Cover Image: May 2005 Scientific American Magazine See Inside

Molecular Treasure Hunt [Preview]

A software tool elicits previously undiscovered gene or protein pathways by combing through hundreds of thousands of journal articles















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When Andrey Rzhetsky arrived at Columbia University as a research scientist in 1996, the first project he collaborated on involved a literature search to try to understand why white blood cells called lymphocytes do not die in chronic lymphocytic leukemia. The mathematician-biologist found a few hundred articles on apoptosis (programmed cell death) and the cancer. Even if he had devoted every moment to the task, it would have been impossible to perform a comprehensive scan of everything that had reached the journals. Worse, "it was just the tip of the iceberg, not nearly enough to understand the whole process," he laments.

The experience led him to an idea that would have made his job on that first project much easier: an automated search tool that could supplant the mind-numbing task of finding and reading all the literature. But it also might do much more; it could even let a machine conduct research on its own, discovering the patterns among the data much as a human would do.


This article was originally published with the title Molecular Treasure Hunt.



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